title: Self-organized critical noise amplification in human closed loop control.
abstract: When humans perform closed loop control tasks like in upright standing or while balancing a stick, their behavior exhibits non-Gaussian fluctuations with long-tailed distributions. The origin of these fluctuations is not known. Here, we investigate if they are caused by self-organized critical noise amplification which emerges in control systems when an unstable dynamics becomes stabilized by an adaptive controller that has finite memory. Starting from this theory, we formulate a realistic model of adaptive closed loop control by including constraints on memory and delays. To test this model, we performed psychophysical experiments where humans balanced an unstable target on a screen. It turned out that the model reproduces the long tails of the distributions together with other characteristic features of the human control dynamics. Fine-tuning the model to match the experimental dynamics identifies parameters characterizing a subject's control system which can be independently tested. Our results suggest that the nervous system involved in closed loop motor control nearly optimally estimates system parameters on-line from very short epochs of past observations.
authors.affiliation: Institute for Theoretical Physics, University of Bremen Germany.
authors.forename: Felix
authors.initials: F
authors.lastname: Patzelt
authors.forename: Markus
authors.initials: M
authors.lastname: Riegel
authors.forename: Udo
authors.initials: U
authors.lastname: Ernst
authors.forename: Klaus
authors.initials: K
authors.lastname: Pawelzik